4.7 Article

Non-linear associations between metabolic syndrome and four typical heavy metals: Data from NHANES 2011-2018

Journal

CHEMOSPHERE
Volume 291, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chemosphere.2021.132953

Keywords

Heavy metals; Logistic regression; Metabolic syndrome; Restricted cubic splines

Funding

  1. National Natural Science Foundation of China [81872584, 81273078]
  2. National 863 Young Scientist Program [2015AA020940]
  3. Natural Science Foundation of Guang-dong Province [2016A030313138]
  4. Key Projects of Guangzhou Science and Technology Program [201704020056]
  5. Interdisci-plinary Research for First-class Discipline Construction Project of Henan University [2019YLXKJC04]
  6. Scientific Research Project for Uni-versity of Education Bureau of Guangzhou [201831841]
  7. Key Sci-entific Research Project Plan of Henan Province [21A330001]
  8. Yellow River Scholar Fund of Henan University

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This study examines the associations between blood levels of typical heavy metals and metabolic syndrome (MetS) among adults. The findings suggest that higher levels of blood lead, cadmium, and mercury are associated with a lower risk of MetS, while higher levels of blood manganese are associated with a higher risk of MetS in the age group of 30-49 years. Non-linear associations between heavy metal levels and MetS risk were also observed.
Previous studies have found that heavy metals are associated with metabolic syndrome (MetS), although findings are inconsistent. Further, investigations into potential associations that consider age-or gender-specific effects and dose-response associations for metal exposure and MetS are rare. In this study, we explore the associations between blood levels of typical heavy metals [lead (Pb), cadmium (Cd), mercury (Hg) and manganese (Mn)] and MetS among adults using logistic regression analysis and restricted cubic splines (RCS) logistic analysis using data from the US National Health and Nutrition Examination Survey 2011-2018. After adjusting for covariates, higher levels of blood Pb, Cd and Hg were associated with lower risks of MetS in participants overall, and in all subgroup analyses, by logistic regression analysis (all P-values <0.05); in contrast, higher levels of blood Mn had a higher risk of MetS only in the age group of 30-49 years (P-values <0.05). We also found non-linear associations of heavy metal levels in blood with risk of MetS in participants overall, in specific age groups and in both genders, using RCS logistic regressions (all P-values <0.05). In addition, the non-linear associations of Pb and Hg we observed in different subgroups differed. In conclusion, blood levels of four heavy metals were associated with the risk of MetS through a variety of non-linear patterns.

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